Książka Beedea's Performance on Knapsack Problem Hédia Zardi

Beedea's Performance on Knapsack Problem

Autor: Hédia Zardi
Język: Angielski
Oprawa: Miękka
Wydawca: Omniscriptum
Dostępność: Dostępna u dostawcy
Wysyłamy za 5-8 dni
146.40
Most real world problems require the simultaneous optimization of multiple, competing, criteria (or...

Informacje o książce

Autor
Język
Angielski
Oprawa
Książka - Miękka
Data wydania
2018
strony
76
EAN
9786131576164
ISBN
6131576165
Enbook ID
07165112
Wydawca
Waga
122
Wymiary
152 x 229 x 5

Pełny opis

Most real world problems require the simultaneous optimization of multiple, competing, criteria (or objectives). In this case, the aim of a multiobjective resolution approach is to find a number of solutions known as Paretooptimal solutions. Evolutionary algorithms manipulate a population of solutions and thus are suitable to solve multi-objective optimization problems. In addition parallel evolutionary algorithms aim at reducing the computation time and solving large combinatorial optimization problems. In this work we study the performance of the Balanced Explore Exploit Distributed Evolutionary Algorithm (BEEDEA) [1] on the multi-objective Knapsack problem which is a combinatorial optimization problem. BEEDA is implemented after some improvements and tested on the Knapsack problem. Key words: multi-objective optimization, evolutionary algorithms, Knapsack problem, distributed metaheuristics.

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